• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.12
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• pp.1-11
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• 1998

A line profile synthesis method is presented that minimizes the nearest-neighbor crosstalk peak level for high-speed pulse transmission in multi-coupled microstrip signal buses. We adopted the optimization technique for the reflected wave control on bus lines resulting in increasing the average spacing between strip conductors, since in a parallel-conductor bus the crosstalk energy is concentrated at the nearest neighbors of the driven line. The generalized S-matrix technique is applied for the input and output waveform prediction, and crosstalk characteristics of various nonuniform lines synthesized for increasing the average spacing are analyzed by comparing each other. Simulation results demonstrate that the Chebyshev taper with dips is adequate to significantly minimize the crosstalk peak level under the satisfactory waveform integrity since the profile is oriented to evenly reflect significant pulse spectra within the frequency range of pulse.

• Nuclear Engineering and Technology
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• v.45 no.3
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• pp.347-360
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• 2013

This paper presents an experimental investigation of the small-break loss-of-coolant accident (SBLOCA) and the loss-of-feedwater accident (LOFW) in a scaled integral test facility of REX-10. REX-10 is a small integral-type PWR in which the coolant flow is driven by natural circulation, and the RCS is pressurized by the steam-gas pressurizer. The postulated accidents of REX-10 include the system depressurization initiated by the break of a nitrogen injection line connected to the steam-gas pressurizer and the complete loss of normal feedwater flow by the malfunction of control systems. The integral effect tests on SBLOCA and LOFW are conducted at the REX-10 Test Facility (RTF), a full-height full-pressure facility with reduced power by 1/50. The SBLOCA experiment is initiated by opening a flow passage out of the pressurizer vessel, and the LOFW experiment begins with the termination of the feedwater supply into the helical-coil steam generator. The experimental results reveal that the RTF can assure sufficient cooldown capability with the simulated PRHRS flow during these DBAs. In particular, the RTF exhibits faster pressurization during the LOFW test when employing the steam-gas pressurizer than the steam pressurizer. This experimental study can provide unique data to validate the thermal-hydraulic analysis code for REX-10.

• Plant Biotechnology Reports
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• v.5 no.4
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• pp.301-308
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• 2011

This study tested the relative and combined efficacy of ShPx2 and ShPAL transgenes by comparing Nicotiana tabacum hybrids with enhanced levels of $_L$-phenylalanine ammonia lyase (PAL) activity and cationic peroxidase (Prx) activity with transgenic parental lines that overexpress either transgene. The PAL/Prx hybrids expressed both transgenes driven by the 35S CaMV promoter, and leaf PAL and Prx enzyme activities were similar to those of the relevant transgenic parent and seven- to tenfold higher than nontransgenic controls. Lignin levels in the PAL/Prx hybrids were higher than the PAL parent and nontransgenic controls, but not significantly higher than the Prx parent. All transgenic plants showed increased resistance to the necrotrophs Phytophthora parasitica pv. nicotianae and Cercospora nicotianae compared to nontransgenic controls, with a preponderance of smaller lesion categories produced in Prx-expressing lines. However, the PAL/Prx hybrids showed no significant increase in resistance to either pathogen relative to the Prx parental line. These data indicate that, in tobacco, the PAL and Prx transgenes do not act additively in disease resistance. Stacking with Prx did not prevent a visible growth inhibition from PAL overexpression. Practical use of ShPAL will likely require more sophisticated developmental control, and we conclude that ShPx2 is a preferred candidate for development as a resistance transgene.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.689-695
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• 2021

In the current technology-driven era, Small and medium enterprises (SMEs) have been deemed as one of the leading and prominent drivers of sustainable economic progress in emerging and developing economies such as in the Bangladesh context. Hence, it is of significance to understand what might fuel accelerating performance of SME business as increased SME performance will bring about more sustainability and strong development of SME sector within the country, through which more employment is anticipated to be generated. Therefore, the current study examines the impact of three factors: risk-taking, innovativeness, and proactiveness on SME performance in Bangladesh. The study has gathered data from SME entities in Dhaka city of Bangladesh, by applying a non-probability sampling strategy. 250 SME owners were contacted to act as respondents and finally, 180 SME owners fully completed the survey questionnaire, indicating that the final sample size is n=180. SPSS is used as a purpose of testing the hypotheses by considering a 5% significance level as acceptance criteria of the hypothesis. Hierarchical regression analysis was run to understand the impact of control variables and independent variables on SME performance and found that age of business, risk-taking, innovativeness, and proactiveness have an important impact on SME performance in Bangladesh.

• Environmental Engineering Research
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• v.24 no.3
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• pp.404-411
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• 2019

In this study, we designed a data-driven model to predict chlorophyll-a using M5P model tree and extreme learning machine (ELM). The Juksan weir in the Youngsan River has high chlorophyll-a, which is the primary indicator of algal bloom every year. Short-term algal bloom prediction is important for environmental management and ecological assessment. Two models were developed and evaluated for short-term algal bloom prediction. M5P is a classification and regression-analysis-based method, and ELM is a feed-forward neural network with fast learning using the least square estimate for regression. The dataset used in this study includes water temperature, rainfall, solar radiation, total nitrogen, total phosphorus, N/P ratio, and chlorophyll-a, which were collected on a daily basis from January 2013 to December 2016. The M5P model showed that the prediction model after one day had the highest performance power and dropped off rapidly starting with predictions after three days. Comparing the performance power of the ELM model with the M5P model, it was found that the performance power of the 1-7 d chlorophyll-a prediction model was higher. Moreover, in a period of rapidly increasing algal blooms, the ELM model showed higher accuracy than the M5P model.

• Smart Structures and Systems
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• v.32 no.5
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• pp.319-338
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• 2023

The study presents a new hybrid data-driven method by combining radial basis functions neural networks (RBF-NN) with the Jaya algorithm (JA) to provide effective structural health monitoring of arch dams. The novelty of this approach lies in that only one user-defined parameter is required and thus can increase its effectiveness and efficiency, as compared to other machine learning techniques that often require processing a large amount of training and testing model parameters and hyper-parameters, with high time-consuming. This approach seeks rapid damage detection in arch dams under dynamic conditions, to prevent potential disasters, by utilizing the RBF-NNN to seamlessly integrate the dynamic elastic modulus (DEM) and modal parameters (such as natural frequency and mode shape) as damage indicators. To determine the dynamic characteristics of the arch dam, the JA sequentially optimizes an objective function rooted in vibration-based data sets. Two case studies of hyperbolic concrete arch dams were carefully designed using finite element simulation to demonstrate the effectiveness of the RBF-NN model, in conjunction with the Jaya algorithm. The testing results demonstrated that the proposed methods could exhibit significant computational time-savings, while effectively detecting damage in arch dam structures with complex nonlinearities. Furthermore, despite training data contaminated with a high level of noise, the RBF-NN and JA fusion remained the robustness, with high accuracy.

• The Journal of the Acoustical Society of Korea
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• v.19 no.1
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• pp.16-24
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• 2000

In this paper the performance of a closed-loop power control scheme using variable step size decision method for DS/CDMA based-low earth orbit(LEO) mobile satellite systems in which the long round trip delay is a dominant performance degradation factor is evaluated. Because there are fundamental differences in the characteristics between the LEO mobile satellite channel and terrestrial mobile channel, such as long round trip delay and different elevation angle, these factors are considered in channel modeling based on the European Space Agency(ESA) measurement data. Since the round trip delay (from the mobile terminal to the gateway station via satellite) is typically 10∼20ms in low altitude satellite channels, closed-loop power control is much less effective than it is on a terrestrial channel. Thus, the adaptive power control scheme using a variable step size control is essential for overcoming the long round trip delay and fading due to the elevation angle. It is shown that the standard deviation of signal to interference ratio(SIR) adopting a variable step size closed-loop power control scheme is much less than that of a fixed step size closed-loop power control. Furthermore, we have driven the conclusion that the measurement interval of power control commands is optimal choice when it is twice the round trip delay.

• Journal of Information Technology Applications and Management
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• v.21 no.3
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• pp.119-133
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• 2014

Prior to the 2000s, internal control had not been among the high priority issues in the management's agenda. Since then, however, it has become one of the hottest issues, and has received a significant attention as the means of improving the transparency, sustainability, and competitiveness of a company. The objectives of this paper are to examine if there has been any noticeable changes in the level of internal controls of Korean companies before and after the 2010, and to analyze the underlying drivers and issues thereto. Accounting manipulation and moral hazard were among the factors to cause the Korean financial crisis in 1997 and 2008. Since then, the capital market has had a strong pressure on Korean companies to enhance the transparency of management and accounting while the government has made the laws, requirements, and recommendations to alleviate the moral hazard problems of management and enhance the accounting transparency. Both market and government have driven companies to put more priority on the reliability of financial reporting and the compliance of applicable laws and regulations. Thereby, the market and governmental forces has led companies to enhance the level of internal controls which contribute to the reliability of financial reporting and the compliance The pressure on companies to enhance the level of internal controls may be different across industries. The capital market and government experiencing the severe financial crisis in 1997 and 2008 put even more pressure on financial companies such as banks to upgrade the reliability of financial reporting and the compliance of regulations to the global level than on non-financial companies. A survey is performed on the changes in the level of internal controls of 54 major companies consisting of 10 financial and 44 non-financial companies in Korea. The survey results show that the average level of internal controls of Korean companies has noticeably improved and that the change in the level of control environment factor is higher than that of IT control factor. The analysis on the industry differences shows that financial companies increased the level of control environment factor more than non-financial companies did while non-financial companies upgraded the level of IT control factor more than financial companies did relatively. Among internal control categories, the most improved area since the economic crisis is "Risk Assessment." The global best practices for risk management have been developed primarily in the financial industry and then spread to other industries. The general level of control practices of Korean companies has been improving significantly, but still appears below the global advanced practices.

• The Journal of Information Systems
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• v.30 no.1
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• pp.151-177
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• 2021

Purpose This paper aims to improve management performance by effectively responding to production needs and reducing inventory through synchronizing production planning and procurement in the aviation industry. In this study, the differences in production planning and execution were first analyzed in terms of demand, supply, inventory, and process using the big data collected from a domestic aircraft manufacturers. This paper analyzed the problems in procurement and inventory management using legacy big data from ERP system in the company. Based on the analysis, we performed a simulation to derive an efficient procurement and inventory management plan. Through analysis and simulation of operational data, we were able to discover procurement and inventory policies to effectively respond to production needs. Design/methodology/approach This is an empirical study to analyze the cause of decrease in inventory turnover and increase in inventory cost due to dis-synchronize between production requirements and procurement. The actual operation data, a total of 21,306,611 transaction data which are 18 months data from January 2019 to June 2020, were extracted from the ERP system. All them are such as basic information on materials, material consumption and movement history, inventory/receipt/shipment status, and production orders. To perform data analysis, it went through three steps. At first, we identified the current states and problems of production process to grasp the situation of what happened, and secondly, analyzed the data to identify expected problems through cross-link analysis between transactions, and finally, defined what to do. Many analysis techniques such as correlation analysis, moving average analysis, and linear regression analysis were applied to predict the status of inventory. A simulation was performed to analyze the appropriate inventory level according to the control of fluctuations in the production planing. In the simulation, we tested four alternatives how to coordinate the synchronization between the procurement plan and the production plan. All the alternatives give us more plausible results than actual operation in the past. Findings Based on the big data extracted from the ERP system, the relationship between the level of delivery and the distribution of fluctuations was analyzed in terms of demand, supply, inventory, and process. As a result of analyzing the inventory turnover rate, the root cause of the inventory increase were identified. In addition, based on the data on delivery and receipt performance, it was possible to accurately analyze how much gap occurs between supply and demand, and to figure out how much this affects the inventory level. Moreover, we were able to obtain the more predictable and insightful results through simulation that organizational performance such as inventory cost and lead time can be improved by synchronizing the production planning and purchase procurement with supply and demand information. The results of big data analysis and simulation gave us more insights in production planning, procurement, and inventory management for smart manufacturing and performance improvement.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.1
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• pp.32-37
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• 2011

The present study has been conducted to propose an algorithm regarding real-time load estimation of a gas engine-driven heat pump. In the study, thermal load of an indoor unit is estimated in terms of air-side and refrigerant-side. The air-side estimation is based on a typical heat exchanger model and is found to be in good agreement with experimental data. When it comes to the refrigerant-side load, a pressure difference across a valve must be estimated. For the estimation, it is assumed to be proportional to a bigger pressure difference that is available either by measurement or by estimation. Relative good agreement between the air- and refrigerant-sides suggests that the assumption may be plausible for the load estimation. The summed flow rate of all of indoor units is in good agreement with the throughput of the compressor which are calculated from the manufacturer's software. Accordingly, estimated thermal loads are also in good agreement. The proposed algorithm may be further developed for improved control algorithm and fault diagnosis.